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This paper builds on the current studies on data mining’s potential benefits to online learning environments. Many Teaching Academics who are non-experts in data mining techniques however are not able to take advantage of these potential benefits. The objective of this paper is to illustrate how learning analytics is bridging the gap between data mined from Learning Management Systems and teaching practice development in higher education, specifically for Teaching Academics who recently transitioned into online teaching. The authors suggest that bridging this gap is an essential step in the development of online teaching practices and online courses. A customised Dashboard that curates data mined from a university’s LMS is discussed, showcasing the impact on the practices of Teaching Academics. The results from the preliminary exploration suggest that learning analytics can bridge the gap between expert and non-experts of data mining techniques and can become a valuable tool for teaching practice development.

Formative assessment benefits both students and teaching academics. In particular, formative assessment in mathematics subjects enables both students and teaching academics to assess individual performance and understanding through students’ responses. Over the last decade, educational technologies and learning management systems (LMSs) are used to support formative assessment design. In mathematics, this is problematic because of the inflexibility of LMS and educational technology tools. Automating formative assessment generation and marking to support mathematics learning is made possible by utilising specific software and technologies in new ways. This paper proposes a new method of creating mathematics formative assessments using LaTeX and PDF forms in conjunction with a computer algebra system (e.g., Maple), independent of an LMS. This method is implemented in undergraduate mathematics subjects servicing non-mathematics–focused higher education courses. The method generates individualised assessments that are automatically marked. Results show that the method provides the teaching academic with a more efficient way of designing formative mathematics assessments without compromising the effectiveness of the assessment task. This study contributes to the growing research on mathematics in higher education. The implication is an increased understanding of how existing technology, implemented in new ways, can potentially benefit both mathematics students and teaching academics.